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Big Data - An Overview

In this article, we are going to learn about big data, what is big data? Its challenges, software technology used etc? Submitted by Uma Dasgupta, on August 04, 2018

If you haven’t heard all about the excitement around Big Data, then I must say you are not really paying attention. The IT industries are the fastest growing technology markets in the world and inset to significantly transform the way we perceive different aspects of life. To grab a good job at IT sector or to have a good grip in the industry, for those who are currently working, we must always remain updated about ongoing and upcoming trends.

The fact is that big data analytics has become one of the most valuable parts of any modern business and will surely have a prominent future in IT sector.

What is big data?

As the name itself suggests us that Big Data means a huge amount of data, which is high volume, high velocity along with a huge variety. Big data requires new technologies to capture, store and analyze them.

In simple language, we can define big data as examining huge amounts of data in order to discover the hidden patterns, correlations, sharpness, prescience market trend etc.

Big data are so voluminous, messed up, varied and complex that the traditional software that we use for data processing is inadequate to deal with.

4 V's of Big Data

The general consensus of the day is that there are specific attributes that define BIG DATA. In the most data circles, these are known as 4 v’s:

1. Volume
2. Variety
3. Velocity
4. Veracity

Figure: Big data analysis

Challenges

Some common challenges faced in Big data analysis are:

• Dealing with data
• Generating insights in a timely manner
• Recruiting and retaining big data
• Integrating disparate data sources
• Validating data
• Storing data
• Securing big data etc

Technologies Used for Big Data

• Different techniques used for analyzing big data are as A/B testing, machine learning, and natural language processing.
• Cloud computing, Artificial intelligence, Database management are also used in big data analysis.
• Charts, graphs etc. of data are used in the analysis process.

Software (Tools) Used for Big Data

• Hadoop: In simple language, we can say that Apache Hadoop is an open source framework which allows us to implement Big Data. Hadoop can be also defined as a distributed data processing system which stores the data and then it allows us to use or process this data in a distributed manner.
  Download link: http://archive.apache.org/dist/hadoop/common/hadoop-2.6.2/hadoop-2.6.2.tar.gz
  Note: It's only the download link for Hadoop, you will have to install Java 8 as well as an eclipse in order to run Hadoop. (** will brief and demonstrate the whole process in upcoming articles).
• Mapreduce: It is a programming paradigm that allows for massive scalability of unstructured data across hundreds or thousands of commodity clusters servers in an Apache Hadoop cluster. It is also called "Heart of the Apache Hadoop".
  Note: There are several others like Apache Spark, NoSQL etc. that are being used for big data analysis.

Conclusion

Till now, we have known what is big data, what are its features, technologies used, certifications that we can do in this field. We will discuss in brief about the difference between data mining and big data, future scopes, more about big data and upcoming trends. So, stay connected, it will be a great fun to learn and discover together. Stay healthy and keep learning!